Abstract: Digital image technology has been extensively applied in many research fields, however, its application is still sparse in entomology. Generally, a digital image may consist of several different objects, and the research interest for an insect image is the insect region in the image. In order to extract the image features for further recognition research, it is necessary to segment the insect region from the origin image. Four algorithms, which are simple thresholding based on image histogram, thresholding based on optimal entropy, thresholding based on fuzzy set entropy and thresholding based on minimal error, respectively, were applied to the segmentation of Helicoverpa armigera image. Results showed that both methods of simple thresholding based on image histogram and thresholding based on fuzzy set entropy can get a satisfactory segmentation of H. armigera image, however, the later one is much more suitable to the practical analysis than others. The segmentation result image of H. armigera after using threshold method based on optimal entropy included too many background pixels, which made it very difficult to extract needed insect image features. The segmentation result image using threshold method based on minimal error is unacceptable, for it can not completely show the striple features of H. armigera. This paper had prepaired some important background materials for further researches of feature extraction and automated image recognition.